Mohamed Helmy | Modeling | Research Excellence Award

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Mohamed Helmy | Modeling | Research Excellence Award

Dr. Mohamed Helmy at university of saienza | Italy

Mohamed Helmy is a Ph.D. researcher in geodesy, hydrography, Earth observation, and remote sensing, with a strong focus on sea-level analysis and tidal modeling. His research integrates in situ measurements, satellite data, and numerical simulations to improve tidal datum realization and coastal monitoring. He has published studies on tidal characteristics in major harbors across Egypt and the Middle East, supporting maritime safety and coastal management. In parallel, he applies deep learning and transformer-based models to enhance digital terrain models and crop classification accuracy. His work demonstrates interdisciplinary expertise in geospatial analysis, machine learning, and environmental applications.

Citation Metrics (Google Scholar)

10
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Citations
5

Documents
8

h-index
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                         🟦 Citations      🟥 Documents       🟩 h-index

Featured Publications

Syarifah Inayati | Modeling | Research Excellence Award

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Syarifah Inayati | Modeling | Research Excellence Award

Dr. Syarifah Inayati at Universitas Negeri Yogyakarta | Indonesia

Syarifah Inayati is an academic researcher at Universitas Negeri Yogyakarta with expertise in statistics, mathematical finance, and optimization, and a scholarly record that demonstrates strong engagement with advanced quantitative modeling and applied statistical analysis. Her research primarily focuses on time series modeling, particularly Markov Switching Autoregressive (MSAR) and Bayesian time-varying parameter models, which she applies to dynamic economic forecasting and financial market analysis. Several of her studies address financial risk and investment analysis, including stock market contagion between Indonesia and the United States, portfolio analysis using Gaussian mixture distributions with expectation–maximization algorithms, and risk measurement through Value at Risk methods under Bayesian mixture frameworks. Beyond financial applications, she has made notable contributions to socio-economic and public policy research, such as forecasting BPJS health insurance beneficiaries using fuzzy time series methods and modeling the Human Development Index of Central Java using three-parameter gamma regression. Her work in optimization includes nonlinear multiobjective optimization problems solved through Pareto front and weighting approaches, demonstrating methodological depth and versatility. In addition to theoretical and applied research, Syarifah Inayati is actively involved in community service and capacity building, contributing to workshops and training programs on nonparametric analysis, factor analysis, logistic regression, and statistical methods for social sciences and education. With 39 citations, an h-index of 4, and consistent citation growth since 2020, her research reflects a balanced integration of rigorous statistical methodology, interdisciplinary collaboration, and practical relevance. Overall, her scholarly contributions strengthen the application of modern statistical and econometric techniques in finance, economics, public policy, and applied mathematics, while also supporting knowledge dissemination through educational and community-oriented initiatives.

Citation Metrics (Google Scholar)

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30
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10
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Citations
39

h-index
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                             🟦 Citations  🟥 h-index  🟩 i10-index

Featured Publications

Wenyan Wu | Modeling | Best Researcher Award

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Wenyan Wu | Modeling | Best Researcher Award

Dr. Wenyan Wu at Guangdong University of Technology | China

Dr. Wenyan Wu is an emerging researcher whose work focuses on the intersection of artificial intelligence, multimodal learning, and intelligent systems with applications in emotion recognition, sentiment analysis, and human-computer interaction. Since creating her ORCID record in August 2022, Dr. Wu has actively contributed to advancing research in cross-modal data analysis, integrating deep learning frameworks with cognitive and affective computing techniques. Her recent publication, “Modality-Enhanced Multimodal Integrated Fusion Attention Model for Sentiment Analysis” (Applied Sciences, 2025), introduces a novel attention-based fusion approach to improve sentiment analysis accuracy by effectively capturing inter-modal dependencies across text, audio, and visual cues. In “Collaborative Analysis of Learners’ Emotional States Based on Cross-Modal Higher-Order Reasoning” (Applied Sciences, 2024), Dr. Wu explores emotion-aware learning environments, presenting innovative reasoning mechanisms for identifying and analyzing learners’ affective states to enhance adaptive education systems. Her research on “Mask-Wearing Detection in Complex Environments Based on Improved YOLOv7” (Applied Sciences, 2024) demonstrates her interdisciplinary expertise, combining computer vision and deep neural networks to address real-world safety monitoring challenges. Earlier, her foundational study, “A Novel Method for Cross-Modal Collaborative Analysis and Evaluation in the Intelligence Era” (Applied Sciences, 2022), laid the groundwork for her later research by proposing an integrated model for data collaboration across modalities in intelligent environments. Dr. Wu’s scholarly output reflects her strong analytical and technical acumen, emphasizing multimodal integration, attention mechanisms, and deep learning optimization. Her contributions not only advance theoretical understanding but also provide practical frameworks for developing emotionally intelligent and context-aware AI systems, bridging the gap between computational models and human-centered design in modern intelligent applications.

Profile: Orcid 

Featured Publications 

Salem Brahim | Modeling | Best Researcher Award

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Salem Brahim | Modeling | Best Researcher Award

Dr. Salem Brahim, Institut Supérieur des Etudes Technologiques de Gafsa, Tunisia.

Neda Goodarzi | Model Updating | Best Scholar Award

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Neda Goodarzi | Model Updating | Best Scholar Award

Ms. Neda Goodarzi , Best Scholar Award , Iran.

Short Biography 📜

Ms.Neda Goodarzi 🎓 is a dedicated civil engineer specializing in structural health monitoring and model updating. She holds a Ph.D. from Universiti Putra Malaysia 🇲🇾 and an MSc from Khaje Nasir University 🇮🇷. With experience as a software instructor, supervisor, and tour leader, she excels in engineering, education, and multilingual communication. Proficient in ETABS, MATLAB, and ABAQUS, she has participated in national engineering competitions 🏗️ and published Q1 research papers 📖. Known for her patience, intelligence, and determination, she is a passionate academic and professional.

Publication Profile

Google Scholar

Education & Experience 🎓👷

📌 Education:
  • 🎓 Ph.D. in Structural Civil Engineering – Model Updating (UPM, Malaysia, 2020–2024)
  • 🎓 MSc in Structural Civil Engineering – Health Monitoring (Khaje Nasir, Iran, 2016–2018)
  • 🎓 BSc in Civil Engineering (Khaje Nasir, Iran, 2011–2015)
  • 🎓 Diploma in Mathematics (Imamat, Iran, 2008–2011)
📌 Experience:
  • 👩‍🏫 English Teacher (English Institute, 2011–2013)
  • 💻 Software Instructor (ETABS) (University, 2013–2015)
  • 🏗️ Project Supervisor (2015–2017)
  • 🌍 English & Persian Tour Leader (2023–2024/2025)
  • 🏫 English Teacher at Korean Kids Academy (2024–2025)

Summary Suitability

Dr. Neda Goodarzi, a distinguished recipient of theBest Researcher Award, has demonstrated exceptional academic and professional excellence, making her a leading candidate for the Best Scholar Award. With a strong educational foundation, she has pursued advanced research in health monitoring and model updating, contributing significantly to the industry through her innovative work at University of Putra Malaysia (UPM). studies. Her research expertise includes structural health monitoring, civil engineering model updating, and applied engineering software solutions (ETABS). She has effectively translated her academic knowledge into practical applications, supervising project implementations and teaching advanced engineering software.

Professional Development 📈🛠️

Ms.Neda Goodarzi is a skilled civil engineer with expertise in structural health monitoring and model updating 🏗️. She is proficient in ETABS, OpenSEES, SAP, ARTeMIS, AutoCAD, Tekla Structures, MATLAB, ABAQUS, and Ansys 💻. A certified member of the Engineering Council, she has participated in steel and concrete structural workshops 🏢. She has attended national engineering competitions 🏆 and has experience translating ISI research papers 📚. Fluent in English, Malay, Spanish, and Arabic, she combines technical knowledge with strong communication skills 🌍. Passionate about innovation, she continues to expand her expertise.

Research Focus 🔬📊

Ms.Neda Goodarzi research interests lie in structural health monitoring, model updating, and innovative civil engineering techniques 🏗️. She focuses on enhancing the safety, durability, and resilience of structures by developing advanced computational models 🧮. Her work involves finite element analysis, data-driven decision-making, and real-time structural assessment 📡. She actively explores smart materials and sensor-based diagnostics to improve structural performance. Her interdisciplinary approach integrates artificial intelligence with civil engineering 🤖. Passionate about sustainable and earthquake-resistant structures 🌍, she aims to bridge the gap between theory and real-world applications.

Awards & Honors 🏆🎖️

  • 🥇 Top Bachelor’s Student in Civil Engineering
  • 🎖️ Direct Admission to MSc (Exceptional Talent)
  • 🏅 19.5/20 in Master’s Thesis
  • 📜 Q1 Research Publications
  • 🏆 National Engineering Competition Winner (Truss Bridge & Steel Bridge)
  • 🏗️ Participation in SCC Concrete National Competition (2019)
  • 📖 ISI Research Paper Translator

Publication Top Notes

  • “A Review of Health Monitoring and Model Updating of Vibration Dissipation Systems in Structures” by N. Godarzi and F. Hejazi was published in 2020 in Civil Engineering Journal, Vol. 6, No. 3, pp. 418-430.
  • As of now, it has been cited 10 times. 📄📊📅  

 

Yoongu Kang | Computational Thermodynamics | Best Researcher Award

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Yoongu Kang | Computational Thermodynamics | Best Researcher Award

Dr. Yoongu Kang, Seoul National University, South Korea.

Publication profile

Scopus
Orcid

Education

  • Ph.D. in Materials Science and Engineering
    Seoul National University, Seoul, Republic of Korea
    09/2017 – 08/2023

    • Dissertation: Predictive thermodynamic model for surface tension of metallic melts
  • B.Eng. in Materials Engineering with 12-month Co-op internship
    McGill University, Montreal, Canada
    09/2011 – 08/2015

    • Internship at 5N Plus Inc. (Dept. Micro Powder)
    • Internship at McGill University (P2[AM]2 Lab.)
    • Internship at FPInnovations (Dept. Bio-refinery)

Experience

  • Postdoctoral Fellow
    Dept. of Materials Science and Engineering
    Seoul National University, Seoul, Republic of Korea
    09/2023 – Present

    • Conducting research on metallurgical processes and alloy development using computational thermodynamics.
    • Collaborating with the research team to design experiments and analyze data.
    • Mentoring graduate students on their research projects.
  • Junior Production Engineer
    Dept. of Micro Powder
    5N Plus Inc., Montreal, Canada
    09/2015 – 06/2017

    • Executed production processes and maintained operations in the Micro Powder department.
    • Collaborated with cross-functional teams to align production processes with quality standards.
    • Monitored and optimized manufacturing parameters to enhance product quality and cost-effectiveness.

Suitability For The Award

Dr. Yoongu Kang is a highly qualified candidate for the Best Researcher Award due to his significant contributions to the field of Materials Science and Engineering. His research in computational thermodynamics and alloy development, combined with his practical experience in production engineering, positions him as an influential figure in the advancement of metallurgical processes.

Professional Development 

Awards and Honors 

  • Best Paper Award (2022)
    For “Critical thermodynamic assessment of Mo–C, Mo–N, and Mo–C–N systems, and its application to Mo carbo-nitride synthesis,” Journal of Materials Research.
  • Graduate Research Fellowship
    Awarded by Seoul National University for outstanding research performance during Ph.D. studies.
  • McGill University Co-op Award
    Recognized for exceptional performance during internship at 5N Plus Inc.
  • Honors for Academic Excellence
    Awarded for maintaining a high GPA throughout the B.Eng. program at McGill University.

Publications

  • Model for Surface Tension of Pure Liquid Metals: Revisit to Iida’s Model
    Kang, Y., Jung, I.-H. (2024) – Cited by: 0
  • Investigation of Mechanical and Corrosion Properties of New Mg-Zn-Ga Amorphous Alloys for Biomedical Applications
    Bazhenov, V.E., Gorobinskiy, M.V., Bazlov, A.I., … Jung, I.-H. (2024) – Cited by: 0
  • Critical Thermodynamic Assessment of Mo–C, Mo–N, and Mo–C–N Systems, and Its Application to Mo Carbo-Nitride Synthesis
    Kang, Y., Paek, M.-K., Jung, I.-H. (2022) – Cited by: 1
  • Anomalous Dimensionality-Driven Phase Transition of MoTe2 in Van der Waals Heterostructure
    Ryu, H., Lee, Y., Kim, H.-J., … Son, Y.-W., Lee, G.-H. (2021) – Cited by: 20

Dr. Jose Luis Cabellos | DFT Award | Excellence in Research | 9423

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Dr. Jose Luis Cabellos | DFT Award | Excellence in Research

Dr. Jose Luis Cabellos , Polytechnic University of Tapachula , Mexico

Dr. José Luis Cabellos is a distinguished Full Professor and Research Coordinator at the Universidad Politécnica de Tapachula (UPTap) in Chiapas, Mexico. His academic journey is marked by a robust background in computational chemistry and nanothermodynamics, underpinned by his role in the National Mexican System of Researchers (SNII-2) and the State System of Researchers (SEI-6). He holds a Doctor of Science degree in Optical Response in Semiconductors from the Centro de Investigaciones en Óptica, México, and has completed postdoctoral research at the Nano-Bio Spectroscopy Group in Spain. Dr. Cabellos has made significant contributions to the field with over 90 published articles, an h-index of 28, and a notable number of citations.

Profile :

Google Scholar

Education:

  • Doctor of Science (2009): Centro de Investigaciones en Óptica, A.C., León, Gto., Mexico. Dissertation on “Optical Response in Semiconductors.”
  • Postdoctoral Research (2010-2012): Nano-Bio Spectroscopy Group, Universidad del País Vasco/Centro de Física de Materiales and Donostia International Physics Center, Spain.

Work Experience:

  • Full Professor and Research Coordinator (2022-Present): UPTap, Chiapas, Mexico.
  • Postdoctoral Researcher (2010-2012): Nano-Bio Spectroscopy Group, Universidad del País Vasco/Centro de Física de Materiales, Donostia-San Sebastián, Spain.
  • Guest and Associate Editor: Theoretical and Computational Chemistry (Frontiers).
  • Reviewer: ChemPhysChem.

Research Interests:

  • Nanothermodynamics
  • Physicochemistry of surfaces
  • Computational chemistry and modeling
  • Spintronics

Publication Top Notes:

Eyringpy: A program for computing rate constants in the gas phase and in solution

Citation-164

Revisiting the racemization mechanism of helicenes

Citation-128

Coaxial Triple‐Layered versus Helical Be6B11− Clusters: Dual Structural Fluxionality and Multifold Aromaticity

Citation-101

Understanding energy-level alignment in donor–acceptor/metal interfaces from core-level shifts

Citation-98

Dynamical behavior of borospherene: a nanobubble

Citation-93

 

Guillermo Riveros | computational | Best Researcher Award

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Guillermo Riveros | computational | Best Researcher Award

Dr. Guillermo A. Riveros, U.S. Army Engineer Research and Development Center, United States.

Dr. Guillermo A. Riveros is a Research Civil Engineer at the U.S. Army Engineer Research and Development Center (ERDC) in Vicksburg, United States. Since 1992, he has been a subject matter expert in areas such as Water Resources Infrastructure, Fatigue and Fracture Mechanics, Computational Fluid and Solid Mechanics, Structural Assessment of Aging Infrastructure, Bio-inspired Material Engineering, and Large Scale Additive Manufacturing. His innovative research has led to significant advancements in both civil and military engineering fields. 🏗️🔬🌊⚙️

Publication Profile

Scopus

Education and Experience

Dr. Riveros received his BS and MS in Civil Engineering from the University of Puerto Rico at Mayagüez. He also earned an MS in Engineering Mechanics from Mississippi State University and a Ph.D. in Civil Engineering from the University of Missouri-Columbia. He has been with the ERDC since 1992, where he has significantly contributed to advancements in engineering computational modeling and analysis. 🎓📚🛠️

Professional Development

Throughout his career, Dr. Riveros has focused on developing innovative methods for fatigue and corrosion repairs using fiber-reinforced polymers, assessing military infrastructure, and exploring bio-inspired materials like Paddlefish. His work combines field measurements with sophisticated 3D finite element analysis to improve the longevity and efficiency of critical structures. 🧠🔧🛡️

Research Focus

 Dr. Riveros’s research includes cutting-edge areas such as computational and experimental mechanics of tainter gates and miter gates, fatigue and fracture mechanics, and bio-inspired material engineering. He aims to keep pace with rapid scientific and technological developments, producing tools and models that advance civil, military, and environmental research. 🌍🔍⚡

Publications 📚📝

  • Deep Learning-Based Super Resolution Applied to Finite Element Analysis of Fused Deposition Modeling 3D Printing, 2024. 📄🤖
  • Prediction of air filtration efficiency and airflow resistance of air filter media using convolutional neural networks and synthetic data derived from simulated media, 2023. 📄🌬️
  • Multi-axial fatigue behavior of high-strength structural bolts, 2023. 📄🔩
  • Stabilized Electrospun Polyacrylonitrile Fibers for Advancements in Clean Air Technology, 2023. 📄🌫️
  • Alternative High-Performance Fibers for Nonwoven HEPA Filter Media, 2023. 📄🧵
  • Modeling uniform random distributions of nonwoven fibers for computational analysis of composite materials, 2022. 📄📊
  • Basalt Fibers for Underwater Fatigue Repair of Steel Panels, 2022. 📄🌊
  • The effects of deteriorated boundary conditions on horizontally framed miter gates, 2022. 📄🚧
  • Digital twin geometry for fibrous air filtration media, 2021. 📄💡
  • Fiber selection for reinforced additive manufacturing, 2021. 📄🖨️